Year: 2025
Type: article
Abstract: Navigating the college admission process in India is often overwhelming for students due to fluctuating cutoff ranks, diverse domains, and the need to consult multiple sources. Traditional methods of college selection rely heavily on manual research, which is time-consuming and error-prone. To address this challenge, NextGen College Advisor leverages machine learning specifically the Random Forest algorithm to predict students' admission chances based on historical KCET cutoff trends. The platform offers real-time, category-specific (General, OBC, SC, ST) predictions across various domains such as engineering, veterinary, and agriculture. It features secure OTP-based authentication, an intuitive dashboard, and multilingual support to enhance accessibility. By automating data analysis and college recommendation, the system minimizes human effort, increases prediction accuracy, and empowers students with personalized guidance for informed decision-making.
Author: Dr. B. M. Vidyavathi
Institution: Ballari Institute of Technology & Management
Language: English
Subfield: Computer Science Applications
Field: Computer Science
Domain: Physical Sciences
SDG: Quality education
Open Access status: diamond
OpenAlex ID: W4410644180